Save up to $499! Grab all Python courses for $49 or all online courses we’ve ever launched for only $169. Only Feb 11-16. Happy Valentine's!
1. Introduction
Filtering by row
Extracting data by column
Practice using filter() and select()
The pipe operator
Sorting rows


In this chapter, we'll focus on new ways of wrangling data and computing statistics using tidyverse's dplyr package. It contains functions that filter rows, select columns, group data, and compute statistics. If you know SQL, dplyr will come easy: it was inspired by SQL.

As usual, we'll start by examining our data. This time, we'll be dealing with country data, including country names, populations, and areas.


Use glimpse() to check the structure of the countries dataset.

Stuck? Here's a hint!